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A Machine Learning Approach Using Survival Statistics to Predict Graft Survival in Kidney Transplant Recipients: A Multicenter Cohort Study.

Scientific reports
Accurate prediction of graft survival after kidney transplant is limited by the complexity and heterogeneity of risk factors influencing allograft survival. In this study, we applied machine learning methods, in combination with survival statistics, ...

A machine-learning based analysis for the recognition of progressive central hypovolemia.

Physiological measurement
OBJECTIVE: Traditional patient monitoring during surgery includes heart rate (HR), blood pressure (BP) and peripheral oxygen saturation. However, their use as predictors for central hypovolemia is limited, which may lead to cerebral hypoperfusion. Th...
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Detection of lung cancer in exhaled breath with an electronic nose using support vector machine analysis.

Journal of breath research
Lung cancer is one of the most common malignancies and has a low 5-year survival rate. There are no cheap, simple and widely available screening methods for the early diagnostics of lung cancer. The aim of this study was to determine whether analysis...

Brain tumor segmentation using holistically nested neural networks in MRI images.

Medical physics
PURPOSE: Gliomas are rapidly progressive, neurologically devastating, largely fatal brain tumors. Magnetic resonance imaging (MRI) is a widely used technique employed in the diagnosis and management of gliomas in clinical practice. MRI is also the st...

Artificial Intelligence: Threat or Boon to Radiologists?

Journal of the American College of Radiology : JACR
The development and integration of machine learning/artificial intelligence into routine clinical practice will significantly alter the current practice of radiology. Changes in reimbursement and practice patterns will also continue to affect radiolo...

A brain-based account of "basic-level" concepts.

NeuroImage
This study provides a brain-based account of how object concepts at an intermediate (basic) level of specificity are represented, offering an enriched view of what it means for a concept to be a basic-level concept, a research topic pioneered by Rosc...

Learning representations for the early detection of sepsis with deep neural networks.

Computers in biology and medicine
BACKGROUND: Sepsis is one of the leading causes of death in intensive care unit patients. Early detection of sepsis is vital because mortality increases as the sepsis stage worsens.

New insights into olivo-cerebellar circuits for learning from a small training sample.

Current opinion in neurobiology
Artificial intelligence such as deep neural networks exhibited remarkable performance in simulated video games and 'Go'. In contrast, most humanoid robots in the DARPA Robotics Challenge fell down to ground. The dramatic contrast in performance is ma...